Focuses on “knowledge-building communities,” and how the internet changes how we think. People increasingly come to learn things not alone but as part of a group—what everyone else around you believes shapes what you believe. The internet is a catalyst for this process. When a group of people work together to accomplish a task, they form what is called a “community of practice.” Collaboratively constructing knowledge online is a process that takes place in a community of practice. I’ll explain how communities of practice operate, through the work of Jean Lave and Etienne Wenger. The knowledge-building process is strongly supported by elements of the software environment as well as the people working together. This is a kind of “distributed cognition,” and work by Edwin Hutchins can help us understand it better.

Revisits the previous topics (community, collaboration, knowledge building, identity, behavior management, and market forces) and explores what constructive steps are possible for members of online sites, and for designers of those sites, to make the internet better. Education is another important missing ingredient. To understand the internet, people need a more nuanced understanding of the nature of knowledge, free speech, and more.

Addresses how market issues shape what online sites exist and what they become. This is particularly relevant for how sites manage inappropriate content and bad behavior. What kind of behavior management takes place depends on what a site can afford. Today’s commercial sites can’t deliver what is healthy for people or for society, because making key decisions steered by the profit motive doesn’t magically make the right thing happen. We need more public investment in non-profit platforms driven by values.

Uses ideas from the prototype theory of categories to define what a “community” is. Eleanor Rosch showed that categories in the mind are based on “prototypes” or “best examples”—a robin is a better example of a bird than an emu or a penguin. Similarly, we understand the idea of “community” in relation to prototypical communities in our minds like small towns or church groups. Ray Oldenburg’s work on “third places” shows us why we need places that are neither work nor home, and how these supportive communities are designed. The chapter shows how the detailed design features of online spaces can help them serve as third places. Finally, sociological research sheds light on how online communication has reshaped the kinds of community and strong and weak ties we all rely on in our lives.

This chapter discusses key questions to provide a foundation for understanding why quantum computers are different from classical computation: What is computation? How is computation different from calculation? What kinds of tasks can computers perform? What is complexity theory? This chapter discusses the early design and government patronage of computing. Critically, this chapter dispels the commonly-held belief that quantum computers have magical, universal powers to solve problems.

In this chapter we present our recommendations for how the policy landscape in the U.S. and other liberal democracies should respond to the opportunities and challenges brought on by quantum information science. These recommendations are informed by the four scenarios of quantum futures combined with the understanding of technology capabilities we discussed in Part I. We begin this chapter by putting our cards on the table and presenting our policy goals. We then explore how to achieve these goals using traditional policy levers: direct investments, education, and law. We conclude with a discussion of national security issues.

Introduces and outlines The Quantum Age: what are quantum technologies and what are the reasons why different institutions are interested in them now. The introduction discusses scenario analysis, likely scenarios for quantum technology deployment, and the high-level policy implications raised by them.

Presents the approaches to building a quantum computer, the different substrates being used to build a scalable quantum computer, the profound challenges in doing so, and finally, an outlook on how the scientific challenges and economic incentives will shape quantum computing projects.

The history of Quantum Computing and Quantum Cryptography starts with a friendship between Charles Bennett and Stephen Wiesner, two undergraduates at Brandeis University who toyed with ideas for sending information using quantum entanglement, and John Conway's Game of Life, which stimulated interest in cellular automata at MIT in the 1970s and started a generation of computer scientists wondering if the universe might be some massive computer running a simulation of reality. In 1974 MIT professor Ed Fredkin spent his yearlong sabbatical at Caltech, where he learned quantum physics from Richard Feynman while he taught Feynman about computer science. Returning to MIT, Fredkin's ideas developed into the philosophy of digital physics, which blossomed into the 1981 Conference on Physics and Computation at MIT. Feynman's keynote at the conference described how a computer based on quantum mechanics principles could compute physics simulations much faster than today's classical compu

This appendix explains quantum effects: uncertainty, entanglement, and superposition; and explains how these effects form the basis of quantum sensing, computing and communication. This appendix summarizes the history and debates of wave mechanics, which was developed at the start of the Twentieth Century. Examples are given of macro-level quantum effects that the reader can observe in an attempt to start building an intuitive sense of quantum effects. These macro-level quantum phenomena are the dual-slit experiment, black-body radiation, and the characteristics of polarized light. Much attention is given to the characteristics of light, both because light provides examples of quantum effects but also because photonic emitters and sensors play a key role in quantum sensing, computing, and communication.